Physical Function and Survival in Older Adults: A longitudinal study accounting for time-varying effects.

PURPOSE OF THE STUDY: Variation in physical function in older adults over time raises several methodological challenges in the study of its association with survival, many of which have largely been overlooked in previous studies. The objective of this study is to examine the relationship between time-varying measures of physical function and survival in men and women aged 70 years and over, while accounting for the time-varying effects of health and lifestyle characteristics. METHODS: 1,846 women and 1,245 men in the Cardiovascular Health Study followed annually for up to 10 years beginning at age 70-74 years were included. We estimated the effect of gait speed and grip strength on survival over the subsequent year, using age as the timescale. RESULTS: A 0.1m/s higher gait speed was associated with a 12% decrease in the likelihood of death in the subsequent year among women (HR 0.88, 95% CI 0.82-0.94). There was no statistically significant effect of gait speed on survival among men (HR 0.97, 95% CI 0.91 to 1.03), or of grip strength on survival among women (HR 0.97, 95% CI 0.95-1.00) or men (HR 0.99, 95% CI 0.97-1.01), over one year. CONCLUSIONS: Upon using time-varying measures of physical function while accounting for time-varying effects of health and lifestyle characteristics, higher gait speed was associated with increased survival among the women in our study. We found no evidence of an association between gait speed and one-year survival in men, or between grip strength and one-year survival in women or men.

The association between physical function and proximity to death in older adults: a multilevel analysis of 4,150 decedents from the Cardiovascular Health Study.

PURPOSE: When examining whether poor physical function is a risk factor for imminent death in older adults, one challenge is the lack of a meaningful time origin, a time point on which the estimate of time-to-death is anchored. In this study, we overcame this challenge by discarding the traditional-and flawed-approach of survival analysis with "time since beginning of follow up" as the time variable, and instead used a novel analytic approach that uses time-to-death as a covariate to examine its association with physical function. METHODS: Physical function and other covariates were measured annually in the Cardiovascular Health Study on 4150 individuals followed up to their time of death. Using multilevel models, we estimated gait speed and grip strength in relation to two time axes: age and proximity to death. RESULTS: As individuals approached death, both gait speed and grip strength decreased significantly. However, after adjustment for health and lifestyle covariates, there was significant variation in the level of physical function between individuals. CONCLUSION: Although physical function was significantly associated with time-to-death, there was significant variation in level of physical function between individuals at comparable proximity to death. A better understanding of these variations is needed before measures of physical function are recommended as a clinical tool for identifying individuals at high risk of death.

Can a Healthy Lifestyle Compress the Disabled Period in Older Adults?

OBJECTIVES: To determine whether lifestyle factors, measured late in life, could compress the disabled period toward the end of life. DESIGN: Community-based cohort study of older adults followed from 1989 to 2015. SETTING: Four U.S. communities. PARTICIPANTS: Community-living men and women aged 65 and older (N = 5,248, mean age 72.7 ± 5.5, 57% female, 15.2% minority) who were not wheelchair dependent and were able to give informed consent at baseline. MEASUREMENTS: Multiple lifestyle factors, including smoking, alcohol consumption, physical activity, diet, body mass index (BMI), social networks, and social support, were measured at baseline. Activities of daily living (ADLs) were assessed at baseline and throughout follow-up. Years of life (YoL) was defined as years until death. Years of able life (YAL) was defined as years without any ADL difficulty. YAL/YoL%, the proportion of life lived able, was used to indicate the relative compression or expansion of the disabled period. RESULTS: The average duration of disabled years was 4.5 (out of 15.4 mean YoL) for women and 2.9 (out of 12.4 mean YoL) for men. In a multivariable model, obesity was associated with 7.3 percentage points (95% confidence interval (CI) = 5.4-9.2) lower YAL/YoL% than normal weight. Scores in the lowest quintile of the Alternate Healthy Eating Index were associated with a 3.7% (95% CI = 1.6-5.9) lower YAL/YoL% than scores in the highest quintile. Every 25 blocks walked in a week was associated with 0.5 percentage points (95% CI = 0.3-0.8) higher YAL/YoL%. CONCLUSION: The effects of healthy lifestyle factors on the proportion of future life lived free of disability indicate that the disabled period can be compressed, given the right combination of these factors.

Sex, Race, and Age Differences in Observed Years of Life, Healthy Life, and Able Life among Older Adults in The Cardiovascular Health Study.

OBJECTIVE: Longevity fails to account for health and functional status during aging. We sought to quantify differences in years of total life, years of healthy life, and years of able life among groups defined by age, sex, and race. DESIGN: Primary analysis of a cohort study. SETTING: 18 years of annual evaluations in four U.S. communities. PARTICIPANTS: 5888 men and women aged 65 and older. MEASUREMENTS: Years of life were calculated as the time from enrollment to death or 18 years. Years of total, healthy, and able life were determined from self-report during annual or semi-annual contacts. Cumulative years were summed across each of the age and sex groups. RESULTS: White women had the best outcomes for all three measures, followed by white men, non-white women, and non-white men. For example, at the mean age of 73, a white female participant could expect 12.9 years of life, 8.9 of healthy life and 9.5 of able life, while a non-white female could expect 12.6, 7.0, and 8.0 years, respectively. A white male could expect 11.2, 8.1, and 8.9 years of life, healthy life, and able life, and a non-white male 10.3, 6.2, and 7.9 years. Regardless of starting age, individuals of the same race and sex groups spent similar amounts (not proportions) of time in an unhealthy or unable state. CONCLUSION: Gender had a greater effect on longevity than did race, but race had a greater effect on years spent healthy or able. The mean number of years spent in an unable or sick state was surprisingly independent of the lifespan.

Brain imaging findings in elderly adults and years of life, healthy life, and able life over the ensuing 16 years: the Cardiovascular Health Study.

OBJECTIVES: To determine whether elderly people with different patterns of magnetic resonance imaging (MRI) findings have different long-term outcomes. DESIGN: Longitudinal cohort study. SETTING: Cardiovascular Health Study. PARTICIPANTS: Individuals aged 65 and older were recruited (N = 5,888); 3,660 of these underwent MRI, and 3,230 without a stroke before MRI were included in these analyses. MEASUREMENTS: Cluster analysis of brain MRI findings was previously used to define five clusters: normal, atrophy, simple infarct, leukoaraiosis, and complex infarct. Participants were subsequently classified as healthy if they rated their health as excellent, very good, or good and as able if they did not report any limitations in activities of daily living (ADLs). Mean years of life (YoL), years of healthy life (YHL), and years of able life (YAL) were calculated over 16 years after the MRI and compared between clusters using unadjusted and adjusted regression analyses. RESULTS: Mean age of participants was 75.0. With 16 years of follow-up, mean YoL was 11.3; YHL, 8.0; and YAL, 8.4. Outcomes differed significantly between clusters. With or without adjustments, outcomes were all significantly better in the normal than complex infarct cluster. The three remaining clusters had intermediate results, significantly different from the normal and complex infarct clusters but not usually from one another. Over 16 years of follow-up, participants in the complex infarct cluster (n = 368) spent the largest percentage of their 8.4 years alive being sick (38%) and not able (38%). CONCLUSION: Findings on MRI scans in elderly adults are associated not only with long-term survival, but also with long-term self-rated health and limitation in ADLs. The combination of infarcts and leukoaraiosis carried the worst prognosis, presumably reflecting small vessel disease.

Decline in health for older adults: five-year change in 13 key measures of standardized health.

BACKGROUND: The health of older adults declines over time, but there are many ways of measuring health. It is unclear whether all health measures decline at the same rate or whether some aspects of health are less sensitive to aging than others. METHODS: We compared the decline in 13 measures of physical, mental, and functional health from the Cardiovascular Health Study: hospitalization, bed days, cognition, extremity strength, feelings about life as a whole, satisfaction with the purpose of life, self-rated health, depression, digit symbol substitution test, grip strength, activities of daily living, instrumental activities of daily living, and gait speed. Each measure was standardized against self-rated health. We compared the 5-year change to see which of the 13 measures declined the fastest and the slowest. RESULTS: The 5-year change in standardized health varied from a decline of 12 points (out of 100) for hospitalization to a decline of 17 points for gait speed. In most comparisons, standardized health from hospitalization and bed days declined the least, whereas health measured by activities of daily living, instrumental activities of daily living, and gait speed declined the most. These rankings were independent of age, sex, mortality patterns, and the method of standardization. CONCLUSIONS: All of the health variables declined, on average, with advancing age, but at significantly different rates. Standardized measures of mental health, cognition, quality of life, and hospital utilization did not decline as fast as gait speed, activities of daily living, and instrumental activities of daily living. Public health interventions to address problems with gait speed, activities of daily living, and instrumental activities of daily living may help older adults to remain healthier in all dimensions.

Accommodation of missing data in supportive and palliative care clinical trials.

PURPOSE OF REVIEW: Clinical trials to evaluate the supportive and palliative care treatments have some different missing data concerns than the other clinical trials. This study reviews the literature on missing data as it may apply to these trials. RECENT FINDINGS: Prevention of missing data through study design and conduct is a recent area of focus. Missing data can be minimized by simplifying trial participation for patients, their caregivers, and trialists. Run-in periods with active drug or collecting data from observer (proxy) respondents may complicate a trial but may be used to address some specific concerns. Many analyses can accommodate data missing because of nonresponse by multiple imputation, using carefully chosen imputation models. Analysis of trials evaluating end-of-life care should distinguish between missing data and truncation because of death. SUMMARY: Likely patterns for missing data should be discussed when planning a clinical trial, as modifications to trial design can minimize missing data while still addressing study aims. Many statistical analysis methods are available to accommodate missing data, but robustness of study conclusions to assumptions about mechanisms underlying the missingness should be evaluated by sensitivity analyses.

A randomized trial to improve communication about end-of-life care among patients with COPD.

OBJECTIVE: Patients with COPD consistently express a desire to discuss end-of-life care with clinicians, but these discussions rarely occur. We assessed whether an intervention using patient-specific feedback about preferences for discussing end-of-life care would improve the occurrence and quality of communication between patients with COPD and their clinicians. METHODS: We performed a cluster-randomized trial of clinicians and patients from the outpatient clinics at the Veterans Affairs Puget Sound Health Care System. Using self-reported questionnaires, we assessed patients' preferences for communication, life-sustaining therapy, and experiences at the end of life. The intervention clinicians and patients received a one-page patient-specific feedback form, based on questionnaire responses, to stimulate conversations. The control group completed questionnaires but did not receive feedback. Patient-reported occurrence and quality of end-of-life communication (QOC) were assessed within 2 weeks of a targeted visit. Intention-to-treat regression analyses were performed with generalized estimating equations to account for clustering of patients within clinicians. RESULTS: Ninety-two clinicians contributed 376 patients. Patients in the intervention arm reported nearly a threefold higher rate of discussions about end-of-life care (unadjusted, 30% vs 11%; P < .001). Baseline end-of-life communication was poor (intervention group QOC score, 23.3; 95% CI, 19.9-26.8; control QOC score, 19.2; 95% CI, 15.9-22.4). Patients in the intervention arm reported higher-quality end-of-life communication that was statistically significant, although the overall improvement was small (Cohen effect size, 0.21). CONCLUSIONS: A one-page patient-specific feedback form about preferences for end-of-life care and communication improved the occurrence and quality of communication from patients' perspectives. TRIAL REGISTRY: ClinicalTrials.gov; No.: NCT00106080; URL: www.clinicaltrials.gov.

Identification of ovarian cancer symptoms in health insurance claims data.

BACKGROUND: Women with ovarian cancer have reported abdominal/pelvic pain, bloating, difficulty eating or feeling full quickly, and urinary frequency/urgency prior to diagnosis. We explored these findings in a general population using a dataset of insured women aged 40-64 and investigated the potential effectiveness of a routine review of claims data as a prescreen to identify women at high risk for ovarian cancer. METHODS: Data from a large Washington State health insurer were merged with the Seattle-Puget Sound Surveillance, Epidemiology and End Results (SEER) cancer registry for 2000-2004. We estimated the prevalence of symptoms in the 36 months prior to diagnosis for early and late-stage ovarian cancer cases and for two comparison groups. The potential performance of a passive screener that would flag women with two or more visits for any of the symptoms in the previous 2-month period was examined. RESULTS: Of the 223,903 insured women, 161 had incident cases of ovarian cancer. Both early and late-stage patients had a higher prevalence of abdominal/pelvic pain and bloating than the comparison groups, primarily in the 3 months before diagnosis. The passive screener had a sensitivity of 0.31 and specificity of 0.83 and usually identified women right before diagnosis. Assuming an average cost of $500 per false positive, the screener would be considered cost-effective if the true positives had an average increase of 8.5 years of life expectancy. CONCLUSIONS: These results support previous findings that ovarian cancer symptoms were reported in health insurance claims and were more prevalent before diagnosis, but the symptoms may occur too close to the diagnosis date to provide useful diagnostic information. The passive screening approach should be reevaluated in the future using electronic medical records; if found to be effective, the method may be potentially useful for other incident diseases.

Longitudinal Data with Follow-up Truncated by Death: Match the Analysis Method to Research Aims.

Diverse analysis approaches have been proposed to distinguish data missing due to death from nonresponse, and to summarize trajectories of longitudinal data truncated by death. We demonstrate how these analysis approaches arise from factorizations of the distribution of longitudinal data and survival information. Models are illustrated using cognitive functioning data for older adults. For unconditional models, deaths do not occur, deaths are independent of the longitudinal response, or the unconditional longitudinal response is averaged over the survival distribution. Unconditional models, such as random effects models fit to unbalanced data, may implicitly impute data beyond the time of death. Fully conditional models stratify the longitudinal response trajectory by time of death. Fully conditional models are effective for describing individual trajectories, in terms of either aging (age, or years from baseline) or dying (years from death). Causal models (principal stratification) as currently applied are fully conditional models, since group differences at one timepoint are described for a cohort that will survive past a later timepoint. Partly conditional models summarize the longitudinal response in the dynamic cohort of survivors. Partly conditional models are serial cross-sectional snapshots of the response, reflecting the average response in survivors at a given timepoint rather than individual trajectories. Joint models of survival and longitudinal response describe the evolving health status of the entire cohort. Researchers using longitudinal data should consider which method of accommodating deaths is consistent with research aims, and use analysis methods accordingly.

Distance as a barrier to using a fitness-program benefit for managed Medicare enrollees.

This study evaluated the effect of distance on the likelihood of initiating and maintaining regular use of a fitness-program benefit in a population of managed Medicare seniors. We studied 8,162 participants and nonparticipants in a managed-care fitness-program benefit: a structured group exercise program or an unstructured health-club membership. Participants in both programs lived significantly closer to facilities than nonparticipants did (structured, p < .001; unstructured, p = .017). Participants living closer to unstructured-program sites attended more frequently than those farther away (p = .008). Distance was not correlated with frequency of use in the structured program (p = .49). Collectively, these analyses demonstrate that distance is related to uptake and, in some cases, continued use of a fitness-program benefit. Health systems providing fitness-program benefits as a way to increase physical activity levels of their plan members should consider location of program facilities in relation to members' home addresses to maximize use of the benefit.

Synchrony of change in depressive symptoms, health status, and quality of life in persons with clinical depression.

BACKGROUND: Little is known about longitudinal associations among measures of depression, mental and physical health, and quality of life (QOL). We followed 982 clinically depressed persons to determine which measures changed and whether the change was synchronous with change in depressive symptoms. METHODS: Data were from the Longitudinal Investigation of Depression Outcomes (LIDO). Depressive symptoms, physical and mental health, and quality of life were measured at baseline, 6 weeks, 3 months, and 9 months. Change in the measures was examined over time and for persons with different levels of change in depressive symptoms. RESULTS: On average, all of the measures improved significantly over time, and most were synchronous with change in depressive symptoms. Measures of mental health changed the most, and physical health the least. The measures of change in QOL were intermediate. The 6-week change in QOL could be explained completely by change in depressive symptoms. The instruments varied in sensitivity to changes in depressive symptoms. CONCLUSION: In clinically depressed persons, measures of physical health, mental health, and quality of life showed consistent longitudinal associations with measures of depressive symptoms.

Public health surveillance of low-frequency populations.

Public health agencies often require data that address the needs of special populations, such as minority groups. Sources of surveillance data often contain insufficient numbers of subjects to fully inform health agencies. In this review, we address the problems of and potential approaches for situations with insufficient surveillance data. We use the examples of race and ethnic minority groups throughout our discussion. However, many of the broad issues are applicable to other special groups with low frequency or who are especially hard to reach. Our recommendations are based, in part, on a symposium held in Missouri with the collaboration of state health agency, community, and academic research participants. We review problems in using existing data and collecting new data, especially from nonprobability samples. We also describe fieldwork issues for reaching and collecting information from special populations. Decisions among methods and solutions may require seeking additional resources for surveillance.